ObjectiveTo investigate the epidemiological and clinical characteristics of human bocavirus (HBoV) in hospitalized children with acute lower respiratory tract infection (ALRTI) at a single-center children’s hospital in Shanghai, thereby providing evidence for the diagnosis, treatment, and prevention of HBoV infection. MethodsA retrospective study was conducted on 19 537 hospitalized children with ALRTI at Shanghai Children’s Hospital from January 2021 to December 2023. Multiplex polymerase chain reaction (PCR) combined with capillary electrophoresis was used to detect HBoV and 12 other common respiratory viruses /atypical pathogens. The positive detection rate, demographic characteristics (sex, age), temporal distribution (year, season) of HBoV, as well as the clinical characteristics of severe and non-severe pneumonia were analyzed. ResultsThe overall HBoV-positive rate was 2.57% (503/19 537), with 59.44% (299/503) being single infections and 40.56% (204/503) being co-infections. The positive detection rate was significantly higher in boys than that in girls (2.78% vs 2.33%, χ²=3.88, P=0.049). The highest infection rate was observed in toddlers, followed by infants (χ²=379.57, P<0.001). The positive rate peaked in 2021 and reached its lowest point in 2023 (χ²=45.49, P<0.001), with epidemics mainly prevalent in summer and autumn. The main clinical symptoms were cough (90.06%, 453/503), fever (75.94%, 382/503), and wheezing (39.96%, 201/503). Children with severe pneumonia showed a higher incidence of wheezing compared with the non-severe group (P<0.001), while underlying diseases and co-infections had no significant association with disease severity (P>0.05). ConclusionHBoV was an important pathogen of ALRTI in children, predominantly affecting infants and toddlers, with higher susceptibility in boys and seasonal peaks in autumn and summer. The main clinical manifestations included cough, fever, and wheezing, with wheezing being more prevalent in children with severe pneumonia.

Objective To investigate the dosimetric effects of tumor treating fields(TTFields)patches on different radiotherapy modes for glioblastoma(GBM)patients who wear TTFields patches during radiotherapy,thereby providing dosimetric guidance for determining the appropriate radiotherapy mode.Methods With the TTFields data from GBM patients,artifact-free radiotherapy CT images were obtained utilizing 3D-printed TPU TTFields patches(3D-Print-TTFields)and anthropomorphic phantoms,and then a TTFields-synchronized radiotherapy image model was constructed.Furthermore,the treatment planning system was used to construct a dosimetric calculation model for TTFields-synchronized radiotherapy by simulating and fitting the ray attenuation rate of TTFields patches measured by accelerators.Using these models,3 kinds of radiotherapy plans were simulated and developed.Specifically,P1 simulated the conventional radiotherapy mode;P2 simulated the TTFields-combined radiotherapy mode(TTF-Com-RT),in which patients underwent radiotherapy using the P1 plan while wearing TTFields patches;and P3 simulated the TTFields-synchronized radiotherapy(TTF-Syn-RT)mode where the TTFields patches were worn throughout the entire radiotherapy process.The paired t-test was used to analyze dosimetric parameters such as target dose(D95),average scalp dose(D-skin),conformity index(CI)and homogeneity index(HI)in 3 plans(P1,P2,and P3),as well as the D95 and D-skin parameters for intensity-modulated radiotherapy(IMRT)and volumetric modulated arc therapy(VMAT)techniques in the P3 plan.Results The D95 simulated by P2 decreased by 1.35%as compared with P1(P<0.05),and the D95 simulated by P3 was 1.31%higher than that in P2(P<0.05).Compared with P1,P2 and P3 increased the D-skin by 12.56%and 14.30%,respectively(P<0.05),and the D-skin simulated by P3 increased by 1.55%as compared with P2(P<0.05).However,there were trivial differences in D95 between P3 and P1,CI and HI among all plans,D95 and D-skin between IMRT and VMAT techniques in P3 plan(P>0.05).Conclusion Based on GBM patient data,CT simulation images obtained from 3D-Print-TTFields combined with anthropomorphic phantom are artifact-free and meet radiotherapy requirements.The target and scalp dose differences between TTF-Com-RT and TTF-Syn-RT are less than 2%,and the dosimetric difference of TTF-Syn-RT using IMRT/VMAT techniques is insignificant.Therefore,clinicians can choose radiotherapy modes and techniques according to actual needs.

The 2021 version of the Baveno Ⅶ consensus on portal hypertension and the 2023 guidelines from the European Association for the Study of the Liver define recompensated cirrhosis as the restoration and stabilization of liver function, improvement of liver fibrosis, and absence of decompensated cirrhosis for a long time following effective treatment of the underlying etiology of cirrhosis. Recompensated cirrhosis has become an important research direction in the field with the gradually increasing number of these patients. Temporary recompensation, stable recompensation, and long-term recompensation are the three stages into which patients with cirrhosis are divided, based on varying recompensation stages. Clinical characteristics and prognosis are significantly different among different stages. Patients in the temporary compensation stage have significant fluctuations in their condition and poor stability, with a high risk of recurrent complications. The prognosis of patients in the stable recompensation stage is significantly affected by the cause and the type of initial decompensation event, while the condition of patients in the long-term recompensation stage is more stable, and the long-term prognosis is close to that of compensated cirrhosis. This article aims to summarize and explore the recompensation rates at different stages of liver cirrhosis, the occurrence risk of various complications and liver cancer, and long-term management and treatment following recompensation, providing new directions for future research in this field.

OBJECTIVE To compare the effect of traditional swab sampling method on etiological surveillance of in-fectious diseases for large-scale object surfaces in hospitals and validate the samples processing method based on pre-wet anti-static fabric and modified polyethylene glycol(PEG)precipitation enrichment technology so as to im-prove the capability of early warning of infectious diseases and optimize the environmental surveillance program in the hospitals.METHODS The on-site surveillance was carried out for 8 times in 3 public hospitals(Shenzhen Longgang People's Hospital,the Second People's Hospital of Longgang and Longgang Maternal and Child Health Hospital)from May 2024 to Mar.2025.Totally 23 types of respiratory tract pathogens(18 types of viruses,5 type of pathogenic bacteria)and 6 types of gastrointestinal tract pathogens were simultaneously detected by means of fluorescent quantitative polymerase chain reaction(PCR);the actual isolation rates,etiological spectrum and cycle threshold(Ct)value were compared.The acrylic plate added with standards of different loads of H1NI influ-enza viruses was used as model for laboratory evaluation.The minimum detection limit,sensitivity and repeatabili-ty were observed and compared between the methods.RESULTS The minimum detection limit of both methods was 6.0 × 104 copies/ml,however,the positive rate of nucleic acid testing of the pre-wet fabric method was 100.00％(3/3),higher than 33.33％(1/3)of the swab method;when the low viral load was 6.0× 105 copies/ml,the average concentration of viral nucleic acid of the pre-wet fabric method(X-Ct=36.59)was higher,with the re-peatability(CV=0.99％,＜3.14％)better.The results of the on-site surveillances showed that the total isolation rates of pathogens of the pre-wet fabric method ranged between 42.84％and 64.27％,higher than between 10.71％and 21.43％of the swab method,with the isolated pathogens more abundant,the Ct value lower(P＜0.05).CONCLUSION The pre-wet fabric sampling enrichment method integrated with anti-static fabric sampling and PEG enrichment technology shows higher sensitivity and stability in the etiological surveillance of large-scale object surfaces,raising the isolation rate.

ObjectiveTo compare the clinical features of patients with hepatitis B virus （HBV）-related early-onset liver cancer and those with late-onset liver cancer， to assess the severity of the disease， and to provide a theoretical basis for the early diagnosis and treatment of liver cancer. MethodsA retrospective analysis was performed for 695 patients who were diagnosed with HBV-related liver cancer for the first time in Guangzhou Eighth People’s Hospital， Guangzhou Medical University， from January 2019 to August 2023， among whom 93 had early-onset liver cancer （defined as an age of50 years for female patients and40 years for male patients） and 602 had late-onset liver cancer （defined as an age of ≥50 years for female patients and ≥40 years for male patients）. Related clinical data were collected， including demographic data， clinical symptoms at initial diagnosis， comorbidities， smoking history， drinking history， family history， routine blood test results， biochemical parameters of liver function， serum alpha-fetoprotein（AFP）， virological indicators， coagulation function， and imaging findings. The pan-inflammatory indices neutrophil-to-lymphocyte ratio （NLR）， platelet-to-lymphocyte ratio （PLR）， and lymphocyte-to-monocyte ratio （LMR） were calculated， as well as FIB-4 index， aspartate aminotransferase-to-platelet ratio index （APRI）， S index， Model for End-Stage Liver Disease （MELD） score， Child-Turcotte-Pugh （CTP） score， albumin-bilirubin （AIBL） grade， and Barcelona Clinic Liver Cancer （BCLC） stage. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Wilcoxon rank-sum test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test or Fisher’s exact test were used for comparison of categorical data between two groups. ResultsThere were significant differences between the two groups in the proportion of male patients and the incidence rates of diabetes， hypertension， and fatty liver disease （χ²=6.357， 15.230， 11.467， and 14.204， all P0.05）， and compared with the late-onset liver cancer group， the early-onset liver cancer group had a significantly higher proportion of patients progressing to liver cancer without underlying cirrhosis （χ²=24.657， P0.001） and a significantly higher proportion of patients with advanced BCLC stage （χ²=6.172， P=0.046）. For the overall population， the most common clinical symptoms included abdominal distension， abdominal pain， poor appetite， weakness， a reduction in body weight， edema of both lower limbs， jaundice， yellow urine， and nausea， and 55 patients （7.9%） had no obvious symptoms at the time of diagnosis and were found to have liver cancer by routine reexamination， physical examination suggesting an increase in AFP， or radiological examination indicating hepatic space-occupying lesion； compared with the late-onset liver cancer group， the patients in the early-onset liver cancer group were more likely to have the symptoms of abdominal distension， abdominal pain， and jaundice （all P0.05）. Compared with the late-onset liver cancer group， the early-onset liver cancer group had a significantly larger tumor diameter （Z=2.845， P=0.034）， with higher prevalence rates of multiple tumors and intrahepatic， perihepatic， or distant metastasis （χ²=5.889 and 4.079， both P0.05）， and there were significant differences between the two groups in tumor location and size （χ²=3.948 and 11.317， both P0.05）. Compared with the late-onset liver cancer group， the early-onset liver cancer group had significantly lower FIB-4 index， proportion of patients with HBsAg ≤1 500 IU/mL， and levels of LMR and Cr （all P0.05）， as well as significantly higher positive rate of HBeAg and levels of log₁₀ HBV DNA， AFP， WBC， Hb， PLT， NLR， PLR， TBil， ALT， Alb， and TC （all P0.05）. ConclusionCompared with late-onset liver cancer， patients with early-onset liver cancer tend to develop liver cancer without liver cirrhosis and have multiple tumors， obvious clinical symptoms， and advanced BCLC stage， which indicates a poor prognosis.

OBJECTIVE: To identify the optimal machine learning algorithm for predicting post-stroke epilepsy (PSE) within one year following acute stroke, establish a nomogram model based on this algorithm, and perform external validation to achieve accurate prediction of secondary epilepsy. METHODS: A total of 870 acute stroke patients admitted to the emergency department of Xiang'an Hospital of Xiamen University from June 2019 to June 2023 were enrolled for model development (model group). An external validation cohort of 435 acute stroke patients admitted to the Fifth Hospital of Xiamen during the same period was used to validate the machine learning algorithms and nomogram model. Patients were classified into control and epilepsy groups based on the development of PSE within one year. Clinical and laboratory data, including baseline characteristics, stroke location, vascular status, complications, hematologic parameters, and National Institutes of Health Stroke Scale (NIHSS) score, were collected for analysis. Nine machine learning algorithms such as logistic regression, CN2 rule induction, K-nearest neighbors, adaptive boosting, random forest, gradient boosting, support vector machine, naive Bayes, and neural network were applied to evaluate predictive performance. The area under the curve (AUC) of receiver operator characteristic curve (ROC curve) was used to identify the optimal algorithm. Logistic regression was used to screen risk factors for PSE, and the top 10 predictors were selected to construct the nomogram model. The predictive performance of the model was evaluated using the ROC curve in both the model and validation groups. RESULTS: Among the 870 patients in the model group, 29 developed PSE within one year. Among the nine algorithms tested, logistic regression demonstrated the best performance and generalizability, with an AUC of 0.923. Univariate logistic regression identified several risk factors for PSE, including platelet count, white blood cell count, red blood cell count, glycated hemoglobin (HbA1c), C-reactive protein (CRP), triglycerides, high-density lipoprotein (HDL), aspartate aminotransferase (AST), alanine aminotransferase (ALT), activated partial thromboplastin time (APTT), thrombin time, D-dimer, fibrinogen, creatine kinase (CK), creatine kinase-MB (CK-MB), lactate dehydrogenase (LDH), serum sodium, lactic acid, anion gap, NIHSS score, brain herniation, periventricular stroke, and carotid artery plaque. Further multivariate logistic regression analysis showed that white blood cell count, HDL, fibrinogen, lactic acid and brain herniation were independent risk factors [odds ratio (OR) were 1.837, 198.039, 47.025, 11.559, 70.722, respectively, all P < 0.05]. In the external validation group, univariate logistic regression analysis showed that platelet count, white blood cell count, CRP, triacylglycerol, APTT, D-dimer, fibrinogen, CK, CK-MB, LDH, NIHSS score, and cerebral herniation were risk factors for PSE one year after acute stroke. Further multiple logistic regression analysis showed that APTT and cerebral herniation were independent predictors (OR were 0.587 and 116.193, respectively, both P < 0.05). The nomogram model, constructed using 10 key variables-brain herniation, periventricular stroke, carotid artery plaque, white blood cell count, triglycerides, thrombin time, D-dimer, serum sodium, lactic acid, and NIHSS score-achieved an AUC of 0.908 in the model group and 0.864 in the external validation group. CONCLUSIONS The logistic regression-based prediction model for epilepsy one year after acute stroke, developed using machine learning algorithms, showed optimal predictive performance. The nomogram model based on the logistic regression-derived predictors showed strong discriminative power and was successfully validated externally, suggesting favorable clinical applicability and generalizability.
Humans ; Machine Learning ; Stroke/complications* ; Nomograms ; Epilepsy/etiology* ; Algorithms ; Male ; Female ; Logistic Models ; Middle Aged ; Aged ; Risk Factors ; Bayes Theorem

Objective To investigate the effects of low-dose cone-beam computed tomography (CBCT) scanning protocols on image quality and radiation dose in patients with cervical cancer. Methods A total of 96 patients with cervical cancer who underwent radiotherapy at a hospital between January 2022 and December 2024 were enrolled in this study. Patients were divided into three groups based on CBCT scanning parameters: an ultra-low-dose group (30 cases), a low-dose group (30 cases), and a routine-dose group (36 cases). The tube voltage was set at 120 kV for all groups, while the tube currents were 132, 215, and 675.8 mAs, respectively. The effects of different scanning parameters on image quality, as indicated by spatial resolution, noise, uniformity, low-contrast resolution, and geometric accuracy, were analyzed. The radiation dose in patients under different scanning parameters was measured. An analysis of variance was performed. Results Under the three different scanning parameters, 4-6 clear line pairs were visible in each group. There were no significant differences in spatial resolution or geometric accuracy in different directions among groups (all P > 0.05). However, as the tube current increased, noise, uniformity, and low-contrast resolution decreased. When the tube current increased from 132 mAs to 215 mAs, noise decreased by approximately 33.57%, uniformity by approximately 26.30%, and low-contrast resolution by approximately 30.55%. When the tube current increased from 215 mAs to 675.8 mAs, noise decreased by approximately 35.61%, uniformity by approximately 12.68%, and low-contrast resolution by approximately 19.91%. These differences were statistically significant (all P < 0.05). The radiation doses in patients under different CBCT scanning parameters followed the order of ultra-low-dose group < low-dose group < routine-dose group, and the differences were statistically significant (P < 0.05). Conclusion Reducing the tube current during CBCT scanning does not affect the image spatial resolution or geometric accuracy in cervical cancer patients, has a minimal impact on overall image quality, and effectively reduces the additional radiation dose received by patients.

Objective To investigate the dosimetric effects of tumor treating fields(TTFields)patches on different radiotherapy modes for glioblastoma(GBM)patients who wear TTFields patches during radiotherapy,thereby providing dosimetric guidance for determining the appropriate radiotherapy mode.Methods With the TTFields data from GBM patients,artifact-free radiotherapy CT images were obtained utilizing 3D-printed TPU TTFields patches(3D-Print-TTFields)and anthropomorphic phantoms,and then a TTFields-synchronized radiotherapy image model was constructed.Furthermore,the treatment planning system was used to construct a dosimetric calculation model for TTFields-synchronized radiotherapy by simulating and fitting the ray attenuation rate of TTFields patches measured by accelerators.Using these models,3 kinds of radiotherapy plans were simulated and developed.Specifically,P1 simulated the conventional radiotherapy mode;P2 simulated the TTFields-combined radiotherapy mode(TTF-Com-RT),in which patients underwent radiotherapy using the P1 plan while wearing TTFields patches;and P3 simulated the TTFields-synchronized radiotherapy(TTF-Syn-RT)mode where the TTFields patches were worn throughout the entire radiotherapy process.The paired t-test was used to analyze dosimetric parameters such as target dose(D95),average scalp dose(D-skin),conformity index(CI)and homogeneity index(HI)in 3 plans(P1,P2,and P3),as well as the D95 and D-skin parameters for intensity-modulated radiotherapy(IMRT)and volumetric modulated arc therapy(VMAT)techniques in the P3 plan.Results The D95 simulated by P2 decreased by 1.35%as compared with P1(P<0.05),and the D95 simulated by P3 was 1.31%higher than that in P2(P<0.05).Compared with P1,P2 and P3 increased the D-skin by 12.56%and 14.30%,respectively(P<0.05),and the D-skin simulated by P3 increased by 1.55%as compared with P2(P<0.05).However,there were trivial differences in D95 between P3 and P1,CI and HI among all plans,D95 and D-skin between IMRT and VMAT techniques in P3 plan(P>0.05).Conclusion Based on GBM patient data,CT simulation images obtained from 3D-Print-TTFields combined with anthropomorphic phantom are artifact-free and meet radiotherapy requirements.The target and scalp dose differences between TTF-Com-RT and TTF-Syn-RT are less than 2%,and the dosimetric difference of TTF-Syn-RT using IMRT/VMAT techniques is insignificant.Therefore,clinicians can choose radiotherapy modes and techniques according to actual needs.

OBJECTIVE To compare the effect of traditional swab sampling method on etiological surveillance of in-fectious diseases for large-scale object surfaces in hospitals and validate the samples processing method based on pre-wet anti-static fabric and modified polyethylene glycol(PEG)precipitation enrichment technology so as to im-prove the capability of early warning of infectious diseases and optimize the environmental surveillance program in the hospitals.METHODS The on-site surveillance was carried out for 8 times in 3 public hospitals(Shenzhen Longgang People's Hospital,the Second People's Hospital of Longgang and Longgang Maternal and Child Health Hospital)from May 2024 to Mar.2025.Totally 23 types of respiratory tract pathogens(18 types of viruses,5 type of pathogenic bacteria)and 6 types of gastrointestinal tract pathogens were simultaneously detected by means of fluorescent quantitative polymerase chain reaction(PCR);the actual isolation rates,etiological spectrum and cycle threshold(Ct)value were compared.The acrylic plate added with standards of different loads of H1NI influ-enza viruses was used as model for laboratory evaluation.The minimum detection limit,sensitivity and repeatabili-ty were observed and compared between the methods.RESULTS The minimum detection limit of both methods was 6.0 × 104 copies/ml,however,the positive rate of nucleic acid testing of the pre-wet fabric method was 100.00％(3/3),higher than 33.33％(1/3)of the swab method;when the low viral load was 6.0× 105 copies/ml,the average concentration of viral nucleic acid of the pre-wet fabric method(X-Ct=36.59)was higher,with the re-peatability(CV=0.99％,＜3.14％)better.The results of the on-site surveillances showed that the total isolation rates of pathogens of the pre-wet fabric method ranged between 42.84％and 64.27％,higher than between 10.71％and 21.43％of the swab method,with the isolated pathogens more abundant,the Ct value lower(P＜0.05).CONCLUSION The pre-wet fabric sampling enrichment method integrated with anti-static fabric sampling and PEG enrichment technology shows higher sensitivity and stability in the etiological surveillance of large-scale object surfaces,raising the isolation rate.

The 2021 version of the Baveno Ⅶ consensus on portal hypertension and the 2023 guidelines from the European Association for the Study of the Liver define recompensated cirrhosis as the restoration and stabilization of liver function, improvement of liver fibrosis, and absence of decompensated cirrhosis for a long time following effective treatment of the underlying etiology of cirrhosis. Recompensated cirrhosis has become an important research direction in the field with the gradually increasing number of these patients. Temporary recompensation, stable recompensation, and long-term recompensation are the three stages into which patients with cirrhosis are divided, based on varying recompensation stages. Clinical characteristics and prognosis are significantly different among different stages. Patients in the temporary compensation stage have significant fluctuations in their condition and poor stability, with a high risk of recurrent complications. The prognosis of patients in the stable recompensation stage is significantly affected by the cause and the type of initial decompensation event, while the condition of patients in the long-term recompensation stage is more stable, and the long-term prognosis is close to that of compensated cirrhosis. This article aims to summarize and explore the recompensation rates at different stages of liver cirrhosis, the occurrence risk of various complications and liver cancer, and long-term management and treatment following recompensation, providing new directions for future research in this field.